Related papers: Using Machine Learning to Improve Neutron Identifi…
New deep learning techniques present promising new analysis methods for Imaging Atmospheric Cherenkov Telescopes (IACTs) such as the upcoming Cherenkov Telescope Array (CTA). In particular, the use of Convolutional Neural Networks (CNNs)…
In order to improve Super-Kamiokande's neutron detection efficiency and to thereby increase its sensitivity to the diffuse supernova neutrino background flux, 13 tons of $\rm Gd_2(\rm SO_4)_3\cdot \rm 8H_2O$ (gadolinium sulfate octahydrate)…
In this work, by using the machine learning methods, we study the sensitivities of heavy pseudo-Dirac neutrino $N$ in the inverse seesaw at the high-energy hadron colliders. The production process for the signal is $pp \to \ell N \to 3 \ell…
The purpose of this paper is to explore the use of underwater image enhancement techniques to improve keypoint detection and matching. By applying advanced deep learning models, including generative adversarial networks and convolutional…
Gamma-hadron discrimination based on shower observables is essential for identifying gamma-ray astrophysical sources at the highest energies. In this work, we introduce $P^{\alpha, T}_{\rm tail}$, a new discrimination variable for…
We demonstrate how deep convolutional neural networks can be trained to predict 2+1 D hydrodynamic simulation results for flow coefficients, mean-transverse-momentum and charged particle multiplicity from the initial energy density profile.…
Signatures of neutrino and antineutrino signals from stellar collapse in heavy water detectors are contrasted with those in water detectors. The effects of mixing, especially due to the highly dense matter in the supernova core, are…
JUNO is a multi-purpose neutrino experiment currently under construction in Jiangmen, China. It is primary aiming to determine the neutrino mass ordering. Moreover, its 20\,kt target mass makes it an ideal detector to study neutrinos from…
The research of geoneutrino is a new interdisciplinary subject of particle experiments and geo-science. Potassium-40 ($^\text{40}$K) decays contribute roughly 1/3 of the radiogenic heat of the Earth, but it is still missing from the…
Hyper-Kamiokande is a next-generation multi-purpose neutrino experiment with a primary focus on constraining CP-violation in the lepton sector. It features a diverse science programme that includes neutrino oscillation studies,…
Proton decay searches in the next generation of water Cherenkov detectors, such as Hyper-Kamiokande, are expected to probe the $10^{35}$-year lifetime regime where atmospheric neutrino backgrounds and systematic uncertainties begin to play…
The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is designed to serve as a test bed for new detector technologies in future water and liquid scintillator based neutrino experiments. Located on the Booster Neutrino Beam at…
Baikal-GVD (Gigaton Volume Detector) is a neutrino telescope installed at a depth of 1366 m in Lake Baikal. The expedition of 2023 brought the number of optical modules in the array up to 3492 (including experimental strings). These optical…
The goal of this work is to investigate the possibility of improving current gamma/hadron discrimination based on their shower patterns recorded on the ground. To this end we propose the use of Convolutional Neural Networks (CNNs) for their…
Cherenkov gamma telescope observes high energy gamma rays, taking advantage of the radiation emitted by charged particles produced inside the electromagnetic showers initiated by the gammas, and developing in the atmosphere. The detector…
The Hyper-Kamiokande neutrino detector is set to begin construction in 2020, succeeding Super-Kamiokande as the world's largest water Cerenkov detector. Research and development are well underway for an integrated light injection system for…
We report the first measurement of the atmospheric neutrino-oxygen neutral-current quasielastic (NCQE) cross section in the gadolinium-loaded Super-Kamiokande (SK) water Cherenkov detector. In June 2020, SK began a new experimental phase,…
Recent discoveries by neutrino telescopes, such as the IceCube Neutrino Observatory, relied extensively on machine learning (ML) tools to infer physical quantities from the raw photon hits detected. Neutrino telescope reconstruction…
The Cherenkov Telescope Array (CTA) will be the next generation gamma-ray observatory and will be the major global instrument for very-high-energy astronomy over the next decade, offering 5 - 10 x better flux sensitivity than current…
Using a combination of a preshower detector and a charged particle veto, it is shown that the neural network method is able to provide satisfactory discrimination between photons and hadrons in the case of extremely high particle density…